Part 1: Developing MEDIx and MEDClass

Richard Mitchell (PI), Niamh Shortt, Jamie Pearce, Elizabeth Richardson, Terry Dawson

Funding

• NERC Environment and Human Health programme

• Supported by:• NERC• EA• Defra• MOD• MRC

• The Wellcome Trust• ESRC• BBSRC• EPSRC• HPA

Exploratory award: Multiple environmental classification of areas for researching health inequality

Objectives:

1) To develop a measure of health-related multiple physical environmental deprivation for the UK (small-area level)

1) To determine its utility in researching spatial inequalities in health

Outline

• Objective 1:To develop a measure of health-related multiple physical environmental deprivation for the UK (small-area level)

• WHY?

• HOW?• Over-arching principles• Identification of health-relevant dimensions of

environmental deprivation• Dataset acquisition and processing• Construction of the summary measures:

• Index• Classification

Why?

Spatial health inequalities

• Widening spatial inequalities in health

Why?

Legend

UK_PARLCONS

SMR_allmort

0.693513 - 0.842089

0.842090 - 0.894062

0.894063 - 0.936554

0.936555 - 0.976199

0.976200 - 1.015046

1.015047 - 1.065584

1.065585 - 1.125754

1.125755 - 1.198214

1.198215 - 1.312202

1.312203 - 1.478902

Standardised mortality rate 1999-2003

150

70

100

74

75

76

77

78

79

80

81

1 2 3 4 5 6 7 8 9 10

Poverty group

Spatial health inequalities

• Socioeconomic deprivation ‘explains’ much:

• But, significant proportion remains unexplained…

• … role of the physical environment?• How would we investigate this?

• How would we measure ‘the physical environment’?

Increasing affluenceIn

creasi

ng life e

xpect

ancy

Bri

tain

, m

ale

s and

fem

ale

s;

Dra

wn f

rom

data

in S

haw

et

al. (

20

05

)

Why?

Measures of Multiple Socioeconomic Deprivation:• Carstairs score• Indices of Multiple Deprivation

Socioeconomic deprivation

• Socioeconomic deprivation:• Multi-dimensional, e.g.:

• Poverty• Housing conditions• Material possessions• Employment

Why?

Measures of Multiple Physical Environmental Deprivation?

Environmental deprivation

• Physical environmental deprivation:• Multi-dimensional, e.g.:

• Air pollution• Climate• Radiation• Greenspace

Why?

How?

Over-arching principles

•Health-relevant•Scientifically credible•User-friendly and useful•Repeatable

(Briggs, 2000; Corvalán et al., 2000; Nardo et al., 2008; Sol et al., 1995)

How

?

Development stages

1. Identify health-relevant dimensions of physical environmental deprivation

2. Identify and acquire datasets

3. Render to same geography

5. Test for associations with health outcomes

4. Develop summary measures

How

?

Identify dimensions of environmental deprivation

1. Scoping review• Grey literature• Reference databases

Long list

2. Systematic literature search• Appraisal of health-relevance:

• Methodological rigour• Strength of association with health• Prevalence of health outcome• > 10% UK population exposure

‘Wish list’

How

?

Air pollutants Climate (temperature) Solar UV radiation Greenspace Industrial facilities Drinking water quality Noise ELF radiation (power lines) RF radiation (transmitters) Radon Individual industrial

pollutants Nuclear facilities Contaminated land Food environment Accidents

Evidence for wish-listed factorsH

ow

?

Wish list dimensions Detrimental? Beneficial? Air pollutants Climate (temperature) Solar UV radiation Greenspace Certain industrial facilities Drinking water quality Noise

Dataset acquisition and processingH

ow

?

UVB index (1991-2000)

6.7 - 9.2

9.3 - 10.2

10.3 - 11.2

11.3 - 12.1

12.2 - 13.2

Wish list dimensions Air pollutants

National Atmospheric Emissions Inventory (NAEI) 1 km grids

Climate (temperature)Met Office, 5 km grids

Solar UV radiationUVB Index (Mo & Green, 1974) calculated from Met Office cloud cover data & latitude

GreenspaceGeneralised Land Use Database (GLUD) CORINE Land Cover Data (modelled %)

Industrial facilitiesEuropean Pollutant Emission Register (EPER);facility type and grid ref

Drinking water quality Noise

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Industrial facilities (2001 and 2002)# Waste management sites

!( Metal processing/production plants

Summary of environmental dataH

ow

?

Geography = UK CAS wards:• n = 10,654 (in 2001)• Average population ~5,500

Detrimental factors:• Air pollutants• Proximity to industry• Cold climate

Beneficial factors:• Solar UV radiation• Greenspace availability

Cold, Clean

and Green

Alternative summary measuresH

ow

?

1. An index• a scale or ranking• increasing value reflects

increasing environmental ‘burden’

2. A classification • a label or category• groups areas that share the

same specific types of environmentComplementary uses:

• Dose-response effect?• Health consequences of specific

combinations of environments?

The IndexH

ow

?

Constructing the index H

ow

?

• Aim:• To represent relative ‘level’ of health-related environmental deprivation• To reflect both detrimental and beneficial environments• Unambiguous and easy to interpret

• How to identify better or worse environments?

• A range of options… simplicity guided our choice:

1. Identify wards exposed to each environmental factor at a ‘detrimental’ (or ‘beneficial’) level

2. Index = balance of number of detrimental to number of beneficial exposures experienced by each ward

Constructing the index H

ow

?

Constructing the index H

ow

?

• Effect thresholds?• Arbitrary decision: ‘health-relevant’ level =

highest exposure quintile

(i.e., most exposed 20% of wards in the UK)

0.0

5.1

.15

.2D

ensi

ty

10 15 20 25(first) PW_pm10Increasing PM10

No.

of

ward

s

‘health-relevant’ exposure

1 2 3 4 5

Calculation for each ward:

Detrimental exposures: Score Highest air pollution (any pollutant)? +1 or 0

Highest proximity to industry? +1 or 0

Coldest temperatures? +1 or 0

Beneficial exposures: Highest greenspace availability? -1 or 0

Highest UV levels? -1 or 0

Multiple Environmental Deprivation Index (MEDIx)

-2 to +3

Constructing the index H

ow

?

Constructing the index III

e.g. Rotherhithe, East End of London:

Detrimental exposures: Score Highest air pollution? +1

Highest proximity to industry? +1

Coldest temperatures? 0

Beneficial exposures: Highest greenspace availability? 0

Highest UV levels? 0

MEDIx +2

How

?

MEDIx score

-2

-1

0

+1

+2

+3

0 150 30075km

Multiple Environmental Deprivation Index (MEDIx)H

ow

?

MEDIx score -2 =

Least environmentally deprived wards (‘healthiest’ places, theoretically)

MEDIx score +3 =

Most environmentally deprived wards (‘unhealthiest’ places)

The ClassificationH

ow

?

Cold, Clean

and Green

Constructing the classification H

ow

?

• Aim:• Identify specific types of health-relevant

environment• Group wards that share these

environmental characteristics

Constructing the classification H

ow

?

Environmental dimensions Air pollutants

Climate (temperature)

Solar UV radiation

Greenspace

Certain industrial facilities

Data reduction

(PCA)

Two-step classificatio

n

Evaluate solutions

Classification

MEDClass cluster

1 London and London-esque

2 Industrial

3 Mediocre Green Sprawl

4 Fair-weather Conurbations

5 Cold, Cloudy Conurbations

6 Isolated, Cold and Green

7 Sunny, Clean and Green

0 150 30075km

Multiple Environmental Deprivation Classification (MEDClass)H

ow

?

Clusters = distinct ‘types’ of environment

Wards in cluster 7:• most greenspace• high UV levels• low air pollutant levels

Conclusion

• Yes, it is possible to construct summary measures of multiple environmental deprivation.• Rigorous, well-documented process• Limitations, room for improvement…

• Arbitrary decisions• Data limitations

• Part 2: Testing the utility of MEDIx and MEDClass…

Any questions?

References

• Briggs D, 2000, "Methods for building environmental health indicators", in Decision-making in environmental health Eds C Corvalán, D Briggs, G Zielhuis (E & FN Spon, London) pp 57-76

• Corvalán C, Briggs D, Kjellström T, 2000, "The need for information: environmental health indicators", in Decision-making in environmental health Eds C Corvalán, D Briggs, G Zielhuis (E & FN Spon, London) pp 25-56

• Nardo M, Saisana M, Saltelli A, Tarantola S, Hoffman A, Giovannini E, 2008 Handbook on constructing composite indicators: Methodology and user guide. EC Joint Research Centre & OECD Statistics Directorate and the Directorate for Science, Technology and Industry (OECD Publishing, Paris)

• Mo T, Green AES: A climatology of solar erythema dose. Photochem Photobiol 1974, 20:483-496.

• Shaw M, Davey Smith G, Dorling D, 2005, "Health inequalities and New Labour: how the promises compare with real progress" BMJ 330 1016-1021

• Sol V M, Lammers P E M, Aiking H, de Boer J, Feenstra J F, 1995, "Integrated environmental index for application in land-use zoning" Environmental Management 19 457-467